Challenging Questions

I am an ML engineer working in a startup. My current situation is horrible,I am constantly stressed about getting laid-off(My performance is good,I got promoted a month ago). I came to know that my company will probably lay people off this month,since they are unable to meet targets. Now,I got rejected in four interviews. There is a lot to learn and revise. Stats and probability. Machine learning algos. Deep learning architectures(got rejected because I was unable to explain the architecture of a complex model in detail). DSA(got rejected twice in this round). SQL (got rejected once since I was unable to solve the SQL problem). ML ops(some recruiters ask this as well). With the added pressure of getting laid off,my whole life is turned upside down.I am unable to focus. Every meeting or discussion I attend I feel like people are evaluating me.( This was not the case before). I don't know what to do. It would really help,if you guys share your interview experiences below.

Actual job: export these 1894 user emails into an excel sheet for marketing by EoD please

Challenges faced while working on java projects 1. **Memory Leaks**: One challenge I faced was identifying and fixing memory leaks in a Java application. I used profilers like VisualVM or YourKit to analyze memory usage and identify objects that were not being garbage collected properly. Then, I reviewed the code to ensure proper resource management, such as closing streams and releasing references when they were no longer needed. 2. **Concurrency Issues**: In a multi-threaded Java application, I encountered race conditions and deadlocks. To solve these issues, I carefully reviewed the code to identify critical sections and synchronized access to shared resources using locks or concurrent data structures like ConcurrentHashMap. Additionally, I used tools like Java's built-in concurrency utilities and frameworks like Akka to manage concurrency more effectively. 3. **Performance Bottlenecks**: Optimizing the performance of a Java application was another challenge. I used profilers to identify bottlenecks and hotspots in the code. Then, I applied various optimization techniques such as algorithmic improvements, caching, and tuning JVM parameters like heap size and garbage collection settings to improve overall performance. 4. **Integration with Legacy Systems**: Integrating a Java application with legacy systems using outdated technologies and protocols was challenging. I leveraged libraries like Apache Camel or Spring Integration to abstract away the complexities of communication protocols and data formats. Additionally, I wrote custom adapters and converters to bridge the gap between the modern Java application and legacy systems. 5. **Handling Big Data**: Processing and analyzing large volumes of data efficiently posed a challenge. I used frameworks like Apache Spark or Hadoop to distribute data processing tasks across multiple nodes and scale horizontally. Additionally, I optimized data processing pipe Source: chatgpt

Today, I took a test for the role of Business Analyst at Meesho. The test consisted of three questions, with the first two being moderate in difficulty compared to the third. The first two questions were multiple-choice, requiring me to find bugs in the code. However, the third question was significantly more challenging, as it required writing an advanced SQL query, which was something I had never encountered before. I understand that it's common for startups to set challenging test papers, but I'm looking for advice on how to tackle advanced SQL queries and how to practice them effectively

So, I graduated this year and joined a startup as a frontend developer 6 months back. Previously I had around 9 months of internship experience in 2 startups. When I was doing my 1st internship, it feels like I know everything about frontend development, I really struggled in my 2nd internship as I am somewhat bad in coding part, struggled but at the end of internship, learnt a lot, got job on that skill, not a great CTC but not too bad. Recently, I started interviewing and seeing many posts on twitter, learnt many concepts, a simple http request has so much thing that sometime it goes out of brain, all started with an SDE-2 frontend interview at Plum, where I didn't know anything. I wanted to go for backend but I am not able to even cover whole frontend part. I don't know if it is normal or not but I feel software engineering is not my cup of tea even though I am handling all the frontend stuff at my company and thinking to switch into product side of things(product management). Seeking some advice what should I do?

I am planning to give interview for 3+ years experience. Please write interview question which you have asked in past.java +springboot etc

Hi Folks, Pls write your interview questions here on SQL with the company name u have interviewed...❤️

I will be using a scale of 10 for better quantification. Python : 7/10 SQL: 7/10 PowerBI: 9/10 ML(Pandas): 6/10 PLSQL: 6/10 Advanced Excel: 8/10 Azure Databricks + DataFactory : Started learning Apache Spark: Started learning Communication skills: 9/10 Prior Work Ex: 1.8yrs as a PLSQL developer (started off as a fresher) + one SAP internship of 4months + one Data analyst internship of 1 month Aspiration : Data Engineering Role 1. Is the above techstack enough to get me a good data engineering role? Will I be able to clear the technical rounds at companies like accenture, IBM etc with this profile? I have heard the barrier to entry for data engineering is higher than that of data analyst. 2. Do I need to learn DSA? 3. What salary range do I fall in with this profile? I seek your honest answer. I feel lost. Also, should I focus more on improving my cloud skills or shall I be more competent with my python skills? Which one would pay me off in a better sense financially? I certainly can not focus on all the tools at once.